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test-driven-development

TDDtestingsoftware developmentunit testingcode qualitydevelopment workflowagilerefactoring
⭐ 229.6kπŸ“„ MITπŸ•’ 2026-06-16Source β†—

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Works across Claude Code, Cursor, Codex, Copilot & Antigravity

Test-Driven Development (TDD) is a disciplined software construction methodology where developers define functional requirements through executable test cases before writing implementation logic. By strictly adhering to the Red-Green-Refactor cycle, developers ensure that every line of production code exists solely to satisfy a previously failed test. This prevents over-engineering and keeps codebase complexity minimal. The process mandates that you must observe a test failure before implementing a solution, confirming that the test effectively identifies the missing feature. Once the test passes, you transition to refactoring to remove duplication and clean the internal structure without altering external behavior. This iterative approach replaces manual, ad-hoc verification with a permanent, automated safety net that documents intended behavior while enforcing high code quality through continuous validation.

When to Use This Skill

  • β€’Developing new logic for complex business requirements
  • β€’Applying surgical bug fixes to prevent regression
  • β€’Restructuring existing components during deep refactoring
  • β€’Defining the public API of a new library or module

How to Invoke This Skill

Example prompts that trigger this skill in Claude Code, Cursor, or Antigravity:

  • β€œStart a new feature using TDD
  • β€œFollow the Red-Green-Refactor cycle for this module
  • β€œApply test-driven development to fix this bug
  • β€œWrite a failing test for the new endpoint
  • β€œGuide me through TDD for this refactor

Pro Tips

  • πŸ’‘Always break down complex features into the smallest possible testable units to maintain a fast and effective Red-Green-Refactor cycle.
  • πŸ’‘Utilize the 'Iron Law' religiously: if production code exists without a preceding failing test, delete and restart with TDD for maximum discipline and clarity.
  • πŸ’‘After achieving green, dedicate sufficient time to the 'Refactor' step to improve code design, readability, and performance, ensuring tests remain green throughout.

What this skill does

  • β€’Forces modular design by requiring testable interfaces
  • β€’Eliminates extraneous code not requested by a test
  • β€’Establishes a rapid feedback loop for immediate error detection
  • β€’Maintains a permanent, automated regression suite
  • β€’Ensures documentation of requirements via descriptive test names

When not to use it

  • βœ•Developing short-lived throwaway prototypes
  • βœ•Writing non-functional configuration files
  • βœ•Working with heavily auto-generated codebases

Example workflow

  1. Identify the next increment of desired behavior
  2. Write a minimal test that fails against current code
  3. Execute the test and verify it produces the expected error
  4. Write the absolute minimum code required to make the test pass
  5. Run tests to confirm the green state
  6. Refactor the code structure while keeping tests green

Prerequisites

  • –Unit testing framework configured
  • –Clear understanding of expected behavior
  • –Access to a fast test runner

Pitfalls & limitations

  • !Writing tests after the implementation instead of before
  • !Creating over-engineered code that satisfies more than the current test
  • !Ignoring the Red phase by assuming the test is correct without seeing it fail

FAQ

What if my test passes immediately?
You are testing existing behavior rather than driving new development. Delete the code or the test and restart until you see the test fail.
Can I write production code first if I know what to do?
No. The Iron Law requires deleting any production code written without a failing test first.
How do I know when to stop adding code during the Green phase?
Stop the moment the test passes. Any additional logic without a corresponding test is likely over-engineering or premature optimization.
Is refactoring allowed while the test is failing?
No. Refactoring should only occur after the test is green to ensure you have a stable baseline.

How it compares

Unlike manual testing, which relies on ad-hoc verification, TDD creates an immutable, machine-readable specification that prevents regression and keeps implementation focused.

Source & trust

⭐ 230k starsπŸ“„ MITπŸ•’ Updated 2026-06-16
πŸ“„ Full skill instructions β€” original source: obra/superpowers
# Test-Driven Development (TDD)

## Overview

Write the test first. Watch it fail. Write minimal code to pass.

**Core principle:** If you didn't watch the test fail, you don't know if it tests the right thing.

**Violating the letter of the rules is violating the spirit of the rules.**

## When to Use

**Always:**
- New features
- Bug fixes
- Refactoring
- Behavior changes

**Exceptions (ask your human partner):**
- Throwaway prototypes
- Generated code
- Configuration files

Thinking "skip TDD just this once"? Stop. That's rationalization.

## The Iron Law

NO PRODUCTION CODE WITHOUT A FAILING TEST FIRST


Write code before the test? Delete it. Start over.

**No exceptions:**
- Don't keep it as "reference"
- Don't "adapt" it while writing tests
- Don't look at it
- Delete means delete

Implement fresh from tests. Period.

## Red-Green-Refactor

digraph tdd_cycle {
rankdir=LR;
red [label="RED\nWrite failing test", shape=box, style=filled, fillcolor="#ffcccc"];
verify_red [label="Verify fails\ncorrectly", shape=diamond];
green [label="GREEN\nMinimal code", shape=box, style=filled, fillcolor="#ccffcc"];
verify_green [label="Verify passes\nAll green", shape=diamond];
refactor [label="REFACTOR\nClean up", shape=box, style=filled, fillcolor="#ccccff"];
next [label="Next", shape=ellipse];

red -> verify_red;
verify_red -> green [label="yes"];
verify_red -> red [label="wrong\nfailure"];
green -> verify_green;
verify_green -> refactor [label="yes"];
verify_green -> green [label="no"];
refactor -> verify_green [label="stay\ngreen"];
verify_green -> next;
next -> red;
}


### RED - Write Failing Test

Write one minimal test showing what should happen.

<Good>
test('retries failed operations 3 times', async () => {
let attempts = 0;
const operation = () => {
attempts++;
if (attempts < 3) throw new Error('fail');
return 'success';
};

const result = await retryOperation(operation);

expect(result).toBe('success');
expect(attempts).toBe(3);
});

Clear name, tests real behavior, one thing
</Good>

<Bad>
test('retry works', async () => {
const mock = jest.fn()
.mockRejectedValueOnce(new Error())
.mockRejectedValueOnce(new Error())
.mockResolvedValueOnce('success');
await retryOperation(mock);
expect(mock).toHaveBeenCalledTimes(3);
});

Vague name, tests mock not code
</Bad>

**Requirements:**
- One behavior
- Clear name
- Real code (no mocks unless unavoidable)

### Verify RED - Watch It Fail

**MANDATORY. Never skip.**

npm test path/to/test.test.ts


Confirm:
- Test fails (not errors)
- Failure message is expected
- Fails because feature missing (not typos)

**Test passes?** You're testing existing behavior. Fix test.

**Test errors?** Fix error, re-run until it fails correctly.

### GREEN - Minimal Code

Write simplest code to pass the test.

<Good>
async function retryOperation<T>(fn: () => Promise<T>): Promise<T> {
for (let i = 0; i < 3; i++) {
try {
return await fn();
} catch (e) {
if (i === 2) throw e;
}
}
throw new Error('unreachable');
}

Just enough to pass
</Good>

<Bad>
async function retryOperation<T>(
fn: () => Promise<T>,
options?: {
maxRetries?: number;
backoff?: 'linear' | 'exponential';
onRetry?: (attempt: number) => void;
}
): Promise<T> {
// YAGNI
}

Over-engineered
</Bad>

Don't add features, refactor other code, or "improve" beyond the test.

### Verify GREEN - Watch It Pass

**MANDATORY.**

npm test path/to/test.test.ts


Confirm:
- Test passes
- Other tests still pass
- Output pristine (no errors, warnings)

**Test fails?** Fix code, not test.

**Other tests fail?** Fix now.

### REFACTOR - Clean Up

After green only:
- Remove duplication
- Improve names
- Extract helpers

Keep tests green. Don't add behavior.

### Repeat

Next failing test for next feature.

## Good Tests

| Quality | Good | Bad |
|---------|------|-----|
| **Minimal** | One thing. "and" in name? Split it. | test('validates email and domain and whitespace') |
| **Clear** | Name describes behavior | test('test1') |
| **Shows intent** | Demonstrates desired API | Obscures what code should do |

## Why Order Matters

**"I'll write tests after to verify it works"**

Tests written after code pass immediately. Passing immediately proves nothing:
- Might test wrong thing
- Might test implementation, not behavior
- Might miss edge cases you forgot
- You never saw it catch the bug

Test-first forces you to see the test fail, proving it actually tests something.

**"I already manually tested all the edge cases"**

Manual testing is ad-hoc. You think you tested everything but:
- No record of what you tested
- Can't re-run when code changes
- Easy to forget cases under pressure
- "It worked when I tried it" β‰  comprehensive

Automated tests are systematic. They run the same way every time.

**"Deleting X hours of work is wasteful"**

Sunk cost fallacy. The time is already gone. Your choice now:
- Delete and rewrite with TDD (X more hours, high confidence)
- Keep it and add tests after (30 min, low confidence, likely bugs)

The "waste" is keeping code you can't trust. Working code without real tests is technical debt.

**"TDD is dogmatic, being pragmatic means adapting"**

TDD IS pragmatic:
- Finds bugs before commit (faster than debugging after)
- Prevents regressions (tests catch breaks immediately)
- Documents behavior (tests show how to use code)
- Enables refactoring (change freely, tests catch breaks)

"Pragmatic" shortcuts = debugging in production = slower.

**"Tests after achieve the same goals - it's spirit not ritual"**

No. Tests-after answer "What does this do?" Tests-first answer "What should this do?"

Tests-after are biased by your implementation. You test what you built, not what's required. You verify remembered edge cases, not discovered ones.

Tests-first force edge case discovery before implementing. Tests-after verify you remembered everything (you didn't).

30 minutes of tests after β‰  TDD. You get coverage, lose proof tests work.

## Common Rationalizations

| Excuse | Reality |
|--------|---------|
| "Too simple to test" | Simple code breaks. Test takes 30 seconds. |
| "I'll test after" | Tests passing immediately prove nothing. |
| "Tests after achieve same goals" | Tests-after = "what does this do?" Tests-first = "what should this do?" |
| "Already manually tested" | Ad-hoc β‰  systematic. No record, can't re-run. |
| "Deleting X hours is wasteful" | Sunk cost fallacy. Keeping unverified code is technical debt. |
| "Keep as reference, write tests first" | You'll adapt it. That's testing after. Delete means delete. |
| "Need to explore first" | Fine. Throw away exploration, start with TDD. |
| "Test hard = design unclear" | Listen to test. Hard to test = hard to use. |
| "TDD will slow me down" | TDD faster than debugging. Pragmatic = test-first. |
| "Manual test faster" | Manual doesn't prove edge cases. You'll re-test every change. |
| "Existing code has no tests" | You're improving it. Add tests for existing code. |

## Red Flags - STOP and Start Over

- Code before test
- Test after implementation
- Test passes immediately
- Can't explain why test failed
- Tests added "later"
- Rationalizing "just this once"
- "I already manually tested it"
- "Tests after achieve the same purpose"
- "It's about spirit not ritual"
- "Keep as reference" or "adapt existing code"
- "Already spent X hours, deleting is wasteful"
- "TDD is dogmatic, I'm being pragmatic"
- "This is different because..."

**All of these mean: Delete code. Start over with TDD.**

## Example: Bug Fix

**Bug:** Empty email accepted

**RED**
test('rejects empty email', async () => {
const result = await submitForm({ email: '' });
expect(result.error).toBe('Email required');
});


**Verify RED**
$ npm test
FAIL: expected 'Email required', got undefined


**GREEN**
function submitForm(data: FormData) {
if (!data.email?.trim()) {
return { error: 'Email required' };
}
// ...
}


**Verify GREEN**
$ npm test
PASS


**REFACTOR**
Extract validation for multiple fields if needed.

## Verification Checklist

Before marking work complete:

- [ ] Every new function/method has a test
- [ ] Watched each test fail before implementing
- [ ] Each test failed for expected reason (feature missing, not typo)
- [ ] Wrote minimal code to pass each test
- [ ] All tests pass
- [ ] Output pristine (no errors, warnings)
- [ ] Tests use real code (mocks only if unavoidable)
- [ ] Edge cases and errors covered

Can't check all boxes? You skipped TDD. Start over.

## When Stuck

| Problem | Solution |
|---------|----------|
| Don't know how to test | Write wished-for API. Write assertion first. Ask your human partner. |
| Test too complicated | Design too complicated. Simplify interface. |
| Must mock everything | Code too coupled. Use dependency injection. |
| Test setup huge | Extract helpers. Still complex? Simplify design. |

## Debugging Integration

Bug found? Write failing test reproducing it. Follow TDD cycle. Test proves fix and prevents regression.

Never fix bugs without a test.

## Testing Anti-Patterns

When adding mocks or test utilities, read @testing-anti-patterns.md to avoid common pitfalls:
- Testing mock behavior instead of real behavior
- Adding test-only methods to production classes
- Mocking without understanding dependencies

## Final Rule

Production code β†’ test exists and failed first
Otherwise β†’ not TDD


No exceptions without your human partner's permission.

How to Use This Skill Unit

Option A: Project-Specific (Recommended)

  1. Click "Download" above
  2. In your project, create the directory: .agent/skills/test-driven-development/
  3. Save the file as SKILL.md
  4. The agent will automatically discover the skill based on its description.

Option B: Global Installation (All Agents)

Save the file to these locations to make it available across all projects:

  • Claude Code: ~/.claude/skills/obra/superpowers/test-driven-development/SKILL.md
  • Cursor: ~/.cursor/skills/obra/superpowers/test-driven-development/SKILL.md
  • Antigravity: ~/.gemini/antigravity/skills/obra/superpowers/test-driven-development/SKILL.md

πŸš€ Install with CLI:
npx skills add obra/superpowers

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Take It Further

Maximize your productivity with these powerful resources

πŸ“‹

Define Your Standards

Set up coding standards to ensure this workflow produces consistent, high-quality results.

Browse Rules Library
πŸ“–

Master Workflows

Learn how to create custom workflows, use Turbo Mode, and build your automation library.

Complete Guide

How to use this Skill in Claude Code & Cursor

For Claude Code (CLI)

To use this skill in Claude Code, copy the rule content into your project's custom instructions or follow our Add-Skill CLI guide. This ensures Claude follows your standards during every code generation.

For Cursor & Windsurf

For Cursor or Windsurf, individual skills are best used in the "Rules for AI" section. This specific unit helps the agent avoid testing & quality assurance issues, leading to cleaner, more efficient code.

Why the skill format matters: the standardized Agent Skills format lets your AI agent load detailed instructions only when they are relevant, keeping your prompt clean while improving results.

Source & attribution

This skill is categorized under Testing & Quality Assurance and is published by Jesse Vincent, maintained in obra/superpowers.

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